I wish I could read this, and I wish even more it had been open access or otherwise published in an open way — archive.today can't get behind the firewall, and I can't access it at my university (an R1 institution) either because they don't subscribe to it. It would have been better to post it on a blog or on an archive server, which is a bit ironic maybe given the apparent point of the commentary.
I think some of the results (e.g., in math) that have been achieved using LLMs point to the value of LLMs but the basic idea of this commentary stub is worth taking more seriously. The pressure to publish, not just by hiring and promotion committees, but also by the din of communicative noise due to the number of academics involved, leads to a lot of unsurprising and predictable output.
There's a position that LLMs will supercede humans in academic work and render them unnecessary, but also a position that maybe some of that work, the work replicated by LLMs, is superfluous anyway, something we should be reducing for everyone's benefit.
Large language models are not the problem · HackerTrans
I think some of the results (e.g., in math) that have been achieved using LLMs point to the value of LLMs but the basic idea of this commentary stub is worth taking more seriously. The pressure to publish, not just by hiring and promotion committees, but also by the din of communicative noise due to the number of academics involved, leads to a lot of unsurprising and predictable output.
There's a position that LLMs will supercede humans in academic work and render them unnecessary, but also a position that maybe some of that work, the work replicated by LLMs, is superfluous anyway, something we should be reducing for everyone's benefit.